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# ================================= evir::gpd =============================== #
# Methods for class evir_gpd
#' @export
logLikVec.evir_gpd <- function(object, pars = NULL, ...) {
if (!missing(...)) {
warning("extra arguments discarded")
}
# If the parameter estimates have not been provided in pars then extract
# them from the fitted object
if (is.null(pars)) {
pars <- coef(object)
}
n_pars <- length(pars)
# Threshold exceedances (values that lie above the threshold)
response_data <- object$data
# If trans = FALSE then there are no covariates and object$data contains
# the response data
sigma <- pars["beta"]
xi <- pars["xi"]
# Calculate the loglikelihood contributions
if (any(sigma <= 0)) {
val <- -Inf
} else {
val <- revdbayes::dgp(response_data, loc = object$threshold, scale = sigma,
shape = xi, log = TRUE)
}
# Return the usual attributes for a "logLik" object
attr(val, "nobs") <- nobs(object)
attr(val, "df") <- n_pars
class(val) <- "logLikVec"
return(val)
}
#' @export
nobs.evir_gpd <- function(object, ...) {
return(object$n.exceed)
}
#' @export
coef.evir_gpd <- function(object, ...) {
return(object$par.ests)
}
#' @export
vcov.evir_gpd <- function(object, ...) {
vc <- object$varcov
par_names <- names(coef(object))
dimnames(vc) <- list(par_names, par_names)
return(vc)
}
#' @export
logLik.evir_gpd <- function(object, ...) {
return(logLik(logLikVec(object)))
}
# See evir_methods.R for nobs, coef, vcov, logLik methods for class "gpd"
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